P1266: THE SKIRT CALCULATOR DYNAMICALLY TRACKS IMMUNE RECONSTITUTION AND PREDICTS CLINICAL OUTCOME AFTER HEMATOPOIETIC STEM CELL TRANSPLANTATION
Authors: Yigeng Cao, Xiaowen Gong, Erlie Jiang, Junren Chen
Journal: HemaSphere (2023)

Topic: 22. Stem cell transplantation - Clinical Background: Immune reconstitution after hematopoietic stem cell transplantation (HSCT) is complicated and of vital importance for survival. There has been, however, little consensus on how to quantitatively assess immune reconstitution in real time as part of standard of care. Aims: We aimed to identify the trajectory of immune reconstitution and identify an immune signature for prognosis. Methods: We retrospectively analyzed 11150 post-transplant immune profiles of 1945 patients who underwent HSCT between 2012 and 2020 at two medical centers in China. 1838 (94.5%) of the cases were allogeneic HSCT. We utilized manifold learning to visualize the temporal profiles of immune cell repopulation (integrating neutrophil, total lymphocyte, natural killer (NK), total T, CD4+ T, and B cell counts in the peripheral blood), used grid-search optimization to identify a composite immune signature that was associated with mortality, and then verified the high-risk signature in two independent subsets of the patients. Results: On average, recovery of absolute cell counts was concentrated on the repopulation of CD8+ T cells during the initial two months after transplant. Inter-patient variance of immune status peaked at around day 60 post-transplant, and broad-ranged recovery in NK, CD8+ T, CD4+ T, and B cells initiated afterwards. Using the training set of patients (n = 729), we identified a composite immune signature during days 91 – 180 after allogeneic HSCT that was predictive of early mortality and moreover simplified it into a formula for a Composite Immune Risk Score. When we verified the Composite Immune Risk Score in the validation (n = 284) and test (n = 391) sets of patients, a high score value was found to be associated with hazard ratios of 3.64 (95% C.I. 1.55 – 8.51; P = 0.0014) and 2.44 (95% C.I., 1.22 – 4.87; P = 0.0087), respectively, for early mortality. The high-risk patients were significantly more likely to suffer from non-relapse mortality (hazard ratio (HR), 3.28; 95% C.I., 2.28 – 4.73; P < 0.0001), including infection-related mortality (HR, 3.12; 95% C.I., 1.97 – 4.96; P < 0.0001). A high Composite Immune Risk Score during days 91 – 180 remained an independent risk factor for early mortality after allogeneic HSCT (HR, 1.80; 95% C.I., 1.28 – 2.55; P = 0.00085) in multivariate analysis. Summary/Conclusion: In conclusion, the Composite Immune Risk Score is easy to compute and could identify the high-risk patients of allogeneic HSCT who require targeted effort for prevention and control of infection.Figure. Visualizing the trajectory of post-transplant immune reconstitution. A, Analytic pipeline. B, The gradients of CD8+ T, CD4+ T, B, and NK cell counts in the two-dimensional phase space. The values of the clinical features are indicated by color intensity. C, The gradients of NK, CD8+ T, CD4+ T, and B cell counts along the horizontal and vertical axes. Each plotted value represents how a given coordinate along one of the two axes independently contributed to one of the four clinical features. D, The average trajectory of post-transplant immune reconstitution across the entire SKIRT dataset. The population standard deviations at selected landmark time periods are also plotted. Different time periods are indicated by different colors. Keywords: Immune reconstitution, Hematopoietic cell transplantation